Intelligence, Educational and Learning Capital, and Domain Impact Level of Activities as Predictors of School Achievement

Abstract

Intelligence is a well-supported predictor of school achievement, however, it refers only to the cognitive facet of learning determinants. The aim of this article is to contrast the predictive properties of two comprehensive concepts developed within the actiotope model of giftedness (AMG) with that of intelligence. These concepts are educational and learning capital (ELC) and the domain impact level of activities (DILA), which were contrasted with a nonverbal intelligence measure (Raven’s standard progressive matrices). We investigated N = 90 fourth graders from regular classes in a German urban area. Results showed that achievement in German language was better predicted by ELC and DILA than by intelligence, whereas mathematical achievement was predicted by intelligence and educational and learning capital to similar degrees. The AMG concepts also showed incremental predictive power over intelligence. These findings suggest that ELC and, with some limitation, DILA (a) are well suited for predictions of school achievement and (b) capture valuable different aspects of the learning system than intelligence measures. Implications for education and research are discussed.